Papers
Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing
Sanghamitra Dutta, Dennis Wei, Hazar Yueksel et al.
It’s Not What Machines Can Learn, It’s What We Cannot Teach
Gal Yehuda, Moshe Gabel, Assaf Schuster
Kernel interpolation with continuous volume sampling
Ayoub Belhadji, Rémi Bardenet, Pierre Chainais
Kernelized Stein Discrepancy Tests of Goodness-of-fit for Time-to-Event Data
Tamara Fernandez, Nicolas Rivera, Wenkai Xu et al.
Kernel Methods for Cooperative Multi-Agent Contextual Bandits
Abhimanyu Dubey, Alex ‘Sandy’ Pentland
Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning
Dipendra Misra, Mikael Henaff, Akshay Krishnamurthy et al.
k-means++: few more steps yield constant approximation
Davin Choo, Christoph Grunau, Julian Portmann et al.
Knowing The What But Not The Where in Bayesian Optimization
Vu Nguyen, Michael A. Osborne
Label-Noise Robust Domain Adaptation
Xiyu Yu, Tongliang Liu, Mingming Gong et al.
Landscape Connectivity and Dropout Stability of SGD Solutions for Over-parameterized Neural Networks
Alexander Shevchenko, Marco Mondelli
Laplacian Regularized Few-Shot Learning
Imtiaz Ziko, Jose Dolz, Eric Granger et al.
Latent Bernoulli Autoencoder
Jiri Fajtl, Vasileios Argyriou, Dorothy Monekosso et al.
Latent Space Factorisation and Manipulation via Matrix Subspace Projection
Xiao Li, Chenghua Lin, Ruizhe Li et al.
Latent Variable Modelling with Hyperbolic Normalizing Flows
Joey Bose, Ariella Smofsky, Renjie Liao et al.
Layered Sampling for Robust Optimization Problems
Hu Ding, Zixiu Wang
LazyIter: A Fast Algorithm for Counting Markov Equivalent DAGs and Designing Experiments
Ali Ahmaditeshnizi, Saber Salehkaleybar, Negar Kiyavash
Learnable Group Transform For Time-Series
Romain Cosentino, Behnaam Aazhang
Learning Adversarially Robust Representations via Worst-Case Mutual Information Maximization
Sicheng Zhu, Xiao Zhang, David Evans
Learning Adversarial Markov Decision Processes with Bandit Feedback and Unknown Transition
Chi Jin, Tiancheng Jin, Haipeng Luo et al.
Learning Algebraic Multigrid Using Graph Neural Networks
Ilay Luz, Meirav Galun, Haggai Maron et al.
Learning and Evaluating Contextual Embedding of Source Code
Aditya Kanade, Petros Maniatis, Gogul Balakrishnan et al.
Learning and Sampling of Atomic Interventions from Observations
Arnab Bhattacharyya, Sutanu Gayen, Saravanan Kandasamy et al.
Learning Autoencoders with Relational Regularization
Hongteng Xu, Dixin Luo, Ricardo Henao et al.
Learning Calibratable Policies using Programmatic Style-Consistency
Eric Zhan, Albert Tseng, Yisong Yue et al.
Learning Compound Tasks without Task-specific Knowledge via Imitation and Self-supervised Learning
Sang-Hyun Lee, Seung-Woo Seo